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REQUIREMENT_ID_1800 β€’ 3-DAY_ACTIVE_POLICY

Associate Analyst

Company
Company Training Basket
Type
Opportunity Type Internship
Salary
Stipend / Salary 3.5 LPA
Location
Location Gurugram, Haryana
Posted Date
Posted Date Today
Excel SQL Power BI Tableau Data Cleaning Data Analysis MIS Reporting Communication Problem Solving
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Aptitude Practice Questions Open Resource β†—
Curated set of quantitative and logical reasoning problems to sharpen the analytical skills needed for the first interview round.
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Data Analytics Interview Prep Open Resource β†—
Comprehensive guide covering common data‑analysis interview topics, including SQL queries and Excel functions relevant for the technical round.
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Comprehensive Interview Guide Open Resource β†—
Resource with interview experiences, sample questions, and tips to help candidates navigate the multi‑stage selection process.
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Algorithm & Data Structure Practice Open Resource β†—
Problem‑solving platform to improve coding logic and data manipulation skills, useful for any technical assessment involving SQL or Python.

Graduates with B.Tech, BCA, B.Sc, BBA, B.Com, Statistics, Mathematics, Economics or related fields. Minimum aggregate of 60% (or equivalent CGPA). No active backlogs at the time of joining. Open to freshers and candidates with up to 2 years of relevant experience. Must be able to work on-site in Gurugram.

1
Round 1: Aptitude & Logical Reasoning
2
Round 2: Technical Assessment (SQL/Excel case study)
3
Round 3: HR interview
Training Basket is an emerging data‑driven solutions provider that helps businesses streamline their operations through robust analytics and reporting. Founded a few years ago, the company has quickly built a reputation for delivering actionable insights to clients across retail, finance, and logistics sectors. With a focus on continuous learning, Training Basket invests heavily in upskilling its workforce, encouraging a culture of curiosity and collaboration. The office in Gurugram is a modern workspace equipped with the latest tools, fostering an environment where fresh talent can grow alongside experienced professionals. As an Associate Analyst, you will be the backbone of the data team, responsible for turning raw data into meaningful narratives that drive business decisions. You will work closely with senior analysts and domain experts to understand reporting requirements, collect and cleanse data from multiple sources, and create daily, weekly, and monthly Management Information System (MIS) reports. The role offers exposure to a variety of industries, allowing you to develop a versatile skill set in data handling, visualization, and stakeholder communication. Key Responsibilities: 1. Gather data from internal databases, spreadsheets, and external APIs. 2. Perform data cleaning, validation, and transformation to ensure accuracy. 3. Develop and maintain Excel dashboards for real‑time monitoring. 4. Write SQL queries to extract, aggregate, and manipulate data sets. 5. Design interactive visualizations using Power BI or Tableau for senior management. 6. Prepare daily, weekly, and monthly MIS reports highlighting key performance indicators. 7. Collaborate with cross‑functional teams to understand reporting needs and translate them into technical solutions. 8. Document data pipelines, reporting logic, and standard operating procedures. 9. Identify trends, anomalies, and insights, and present findings in clear, concise formats. 10. Support ad‑hoc analysis requests and contribute to process improvement initiatives. Tech Stack: Microsoft Excel, SQL (MySQL/SQL Server), Power BI, Tableau, basic Python/R for data manipulation (optional). The role emphasizes strong analytical thinking, attention to detail, and effective communication. Growth Path: Starting as an Associate Analyst, high performers can progress to Senior Analyst, then to Team Lead or Data Analytics Manager within 2‑3 years. The company encourages certifications in data tools and offers mentorship programs to accelerate career growth. Why Join Training Basket? You will be part of a fast‑growing firm that values learning, offers hands‑on experience with industry‑standard analytics tools, and provides a clear roadmap for advancement. The on‑site Gurugram location ensures you can network with a vibrant professional community while contributing to impactful projects from day one.

Training Basket β€” Data Analytics & SQL Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC πŸ“–
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource β†—
COMPANY GUIDE 🎯
Training Basket Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Training Basket and off-campus tech roles.

Open Resource β†—
MOCK TESTS & PAPERS πŸ“
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource β†—
CODING PRACTICE πŸ’»
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource β†—
Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (Excel, SQL, Power BI, Tableau, Data Cleaning, Data Analysis, MIS Reporting, Communication, Problem Solving) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
Training Basket Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the difference between WHERE and HAVING clauses in SQL? Answer β–Ό
Model Answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer β–Ό
Model Answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer β–Ό
Model Answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer β–Ό
Model Answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer β–Ό
Model Answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Why do you want to join Training Basket as a Associate Analyst?
Preparation Tip: Highlight Training Basket's market reputation, recent tech innovations, and how your skills in Excel directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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